Multi-scale lattice structure parametric modeling method, device, equipment and medium

Abstract

The invention relates to the technical field of structure modeling, in particular to a multi-scale lattice structure parametric modeling method and device, equipment and a medium. The method comprises the steps that modeling is conducted on a multi-scale lattice structure through SOLIDWORKS software, and a first geometric model is generated; importing the first geometric model into COMSOL software, and adjusting a size variable of the first geometric model to generate a second geometric model; wherein the second geometric model is in a. Stl format, and the second geometric model in the. Stl format is generated by outputting a command stream program of the first geometric model and recompiling the command stream program; importing the second geometric model into MATLAB software, and identifying a constraint surface and a loading surface of the second geometric model through the MATLAB software; and performing finite element analysis on the second geometric model through MATLAB software according to the constraint surface and the loading surface to obtain the stress distribution condition of the multi-scale lattice structure.

Description

Technical Field

[0001] The present invention relates to the technical field of structural modeling, and particularly relates to a multi-scale lattice structure parametric modeling method, device, equipment and medium. Background Art

[0002] With the development of additive manufacturing technology, additive manufacturing lattice structures have received extensive attention. They have characteristics such as light weight, high specific strength, high specific stiffness, and strong designability. Therefore, lattice structures have become a new choice in the field of aerospace research and are currently widely used in parts such as cabin partitions.

[0003] Due to the layer-by-layer stacking manufacturing process, there are many uncertainties that affect the performance of lattice structures. In order to improve the reliability of lattice structures, it is necessary to analyze the stress distribution of additive manufacturing lattice structures and carry out geometric modeling and finite element analysis.

[0004] Traditional modeling and simulation methods require manual input of parameters such as rod diameter, rod length, elastic modulus, Poisson's ratio, etc., which is time-consuming. In order to improve the analysis efficiency and reduce the operation difficulty of staff, it is crucial to seek high-efficiency modeling and simulation methods. Summary of the Invention

[0005] The purpose of the present invention is to provide a multi-scale lattice structure parametric modeling method, device, equipment and medium, which can solve the technical problem of low efficiency in lattice structure modeling and simulation.

[0006] To solve the above technical problem, an embodiment of the present invention provides a multi-scale lattice structure parametric modeling method, including the following steps: Model the multi-scale lattice structure through SOLIDWORKS software to generate a first geometric model of the multi-scale lattice structure; Import the first geometric model into COMSOL software, and adjust the first dimension variable of the first geometric model to a second dimension variable through COMSOL software to generate a second geometric model of the multi-scale lattice structure; wherein, the second geometric model is in.stl format, and the.stl format second geometric model is generated by COMSOL software according to the step of adjusting the first dimension variable to generate a command flow program, and the command flow program is rewritten according to the second dimension variable; Import the second geometric model into MATLAB software, and identify the constraint surface and loading surface of the second geometric model through MATLAB software; Perform finite element analysis on the second geometric model through MATLAB software according to the constraint surface and loading surface to obtain the stress distribution of the multi-scale lattice structure.

[0007] Optionally, the multi-scale lattice structure is modeled by SOLIDWORKS software to generate a first geometric model of the multi-scale lattice structure, including: According to the geometric configuration of the multi-scale lattice structure, use SOLIDWORKS software for modeling, and during the modeling process, use the equation function in SOLIDWORKS software to define the first size variable of the multi-scale lattice structure to generate the first geometric model.

[0008] Optionally, importing the first geometric model into COMSOL software and adjusting the first size variable of the first geometric model to a second size variable by COMSOL software to generate a second geometric model of the multi-scale lattice structure, including: Adopt the combined module COMSOL Multiphysics of SOLIDWORKS software and COMSOL software to import the first geometric model into COMSOL software; Import the defined first size variable of the multi-scale lattice structure into the global definition parameter module of COMSOL software, and generate a command flow file for the steps of setting parameters in the global definition parameter module; Rewrite the command flow program, adjust the first size variable of the first geometric model to the second size variable to generate a second geometric model of the multi-scale lattice structure.

[0009] Optionally, identifying the constraint surface and the loading surface of the second geometric model by MATLAB software, including: Obtain sample geometric models of multi-scale lattice structures with numbers for several constraint surfaces and loading surfaces, and obtain images of the constraint surfaces and loading surfaces of each sample geometric model; wherein, each image contains the number corresponding to the constraint surface or the loading surface; Use the images of the constraint surfaces and loading surfaces of several sample geometric models to train an image recognition model, and input the images of the constraint surfaces and loading surfaces of the second geometric model into the image recognition model to obtain the numbers of the constraint surfaces and loading surfaces of the second geometric model, so as to identify the constraint surfaces and loading surfaces of the second geometric model.

[0010] Optionally, after obtaining the stress distribution of the multi-scale lattice structure, it further includes: Construct a limit state function of the multi-scale lattice structure according to the stress distribution; wherein, the limit state function is used to describe whether the multi-scale lattice structure is in a failure state; Take the Gaussian process model as the surrogate model of the limit state function, use the parameter variables that affect the limit state function value of the multi-scale lattice structure as sampling points, sample along the important direction by the adaptive line sampling method, and use the Gaussian process model to predict the limit state function values at the sampling points. Determine the sampling points that make the multi-scale lattice structure in a failure state according to the values of the limit state function as failure samples, and determine the failure probability of the multi-scale lattice structure according to the number of failure samples.

[0011] An embodiment of the present invention further provides a multi-scale lattice structure parametric modeling device, including: A first model generation module for modeling the multi-scale lattice structure through SOLIDWORKS software to generate a first geometric model of the multi-scale lattice structure; A second model generation module for importing the first geometric model into COMSOL software and adjusting the first dimension variable of the first geometric model to a second dimension variable through COMSOL software to generate a second geometric model of the multi-scale lattice structure; wherein, the second geometric model is in.stl format, and the.stl format second geometric model is generated by COMSOL software according to the steps of adjusting the first dimension variable to generate a command flow program and re-writing the command flow program according to the second dimension variable; A model recognition module for importing the second geometric model into MATLAB software and identifying the constraint surface and the loading surface of the second geometric model through MATLAB software; A model analysis module for performing finite element analysis on the second geometric model according to the constraint surface and the loading surface through MATLAB software to obtain the stress distribution of the multi-scale lattice structure.

[0012] An embodiment of the present invention further provides a computer device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the above-mentioned multi-scale lattice structure parametric modeling method.

[0013] An embodiment of the present invention further provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the above-mentioned multi-scale lattice structure parametric modeling method is implemented.

[0014] The multi-scale lattice structure parametric modeling method provided by the present invention has at least the following beneficial effects: MATLAB can be used for finite element analysis, and then the reliability analysis can be carried out by using the solution results. Therefore, in the present invention, MATLAB software is used to model the multi-scale lattice structure, and the stress distribution of the multi-scale lattice structure is obtained through finite element analysis, so as to analyze the reliability of the multi-scale lattice structure. Specifically, by combining the three software SOLIDWORKS, COMSOL, and MATLAB, the command flow file of COMSOL can be recompiled to complete the reconstruction of the model in SOLIDWORKS, realize the parametric modeling and simulation of the multi-scale lattice structure, reduce the operation difficulty and duration, and then perform the finite element analysis of the lattice structure through MATLAB, which provides strong support for the reliability analysis of the lattice structure and improves the actual efficiency.

[0015] Considering the complex configuration of the lattice structure, the situation where the loading surface and the constraint surface cannot be numbered may occur under multi-scale changes. Therefore, in order to facilitate the parametric finite element analysis of the lattice structure in MATLAB, the present invention improves the lattice structure in advance. Specifically, first, a first geometric model of the multi-scale lattice structure is modeled by SOLIDWORKS software, and then imported into COMSOL software. By changing the size variables of the first geometric model, a second geometric model of the multi-scale lattice structure is generated, and then imported into MATLAB software for numbering the constraint surface and the loading surface, realizing the modeling and simulation of the multi-scale lattice structure by MATLAB software. Among them, the model in the ".stl" format in MATLAB software can be used for finite element analysis. Therefore, in the present invention, COMSOL software is used to generate a command flow program according to the steps of adjusting the first size variable, and the command flow program is rewritten according to the second size variable to generate a second geometric model in the.stl format. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] One or more embodiments are exemplarily illustrated by the pictures in the corresponding drawings, and these exemplary illustrations do not constitute a limitation on the embodiments.

[0017] Figure 1 is a flowchart of a parametric modeling method for a multi-scale lattice structure according to an embodiment of the present invention Figure One ; Figure 2 is a flowchart of a parametric modeling method for a multi-scale lattice structure according to an embodiment of the present invention Figure Two ; Figure 3 is a schematic diagram of a three-dimensional geometric model of a lattice structure according to an embodiment of the present invention; Figure 4 is a schematic diagram of parametric modeling of a single cell of a lattice structure according to an embodiment of the present invention; Figure 5 It is a numbering diagram of a unit cell of a lattice structure and an identification diagram of the loading surface numbers of the overall lattice structure provided according to an embodiment of the present invention. Detailed implementation manners

[0018] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be described in detail below with reference to the accompanying drawings. However, those of ordinary skill in the art can understand that in the embodiments of the present invention, many technical details are provided to help readers better understand the present invention. However, even without these technical details and various changes and modifications based on the following embodiments, the technical solutions claimed by the present invention can still be implemented. The division of the following embodiments is for the convenience of description and should not constitute any limitation to the specific implementation manners of the present invention. The various embodiments can be combined and cross-referenced with each other on the premise of no contradiction.

[0019] An embodiment of the present invention relates to a multi-scale lattice structure parametric modeling method. The implementation details of the multi-scale lattice structure parametric modeling method of this embodiment will be specifically described below. The following content is only the implementation details provided for convenient understanding and is not necessary for implementing this solution.

[0020] The specific process of the multi-scale lattice structure parametric modeling method of this embodiment can be as Figure 1 shown and includes: Step 101, model the multi-scale lattice structure through SOLIDWORKS software to generate a first geometric model of the multi-scale lattice structure.

[0021] Specifically, according to the geometric configuration of the multi-scale lattice structure, use SOLIDWORKS software for modeling, and during the modeling process, utilize the equation function in SOLIDWORKS software to define the size variables of the multi-scale lattice structure, that is, the first size variables, such as rod diameter, rod length, etc., to generate the first geometric model. Among them, when performing finite element analysis in MATLAB, the MATLAB program will number each face of the additive manufacturing lattice structure. Due to the complex configuration of the additive manufacturing lattice structure, under multi-scale changes, there will be situations where the loading surface and the constraint surface cannot be numbered. To facilitate parametric finite element analysis in MATLAB, the additive manufacturing lattice structure is improved in advance, and geometries with a thickness of 0.05 mm are added to the loading surface and the constraint surface.

[0022] This step is used to determine the geometric configuration of the additive manufacturing lattice structure, realize size parameterization within SOLIDWORKS, and at the same time propose improvements to the lattice configuration to achieve parametric modeling under subsequent multi-scale changes.

[0023] Step 102: Import the first geometric model into the COMSOL software, and adjust the first dimension variable of the first geometric model to the second dimension variable through the COMSOL software to generate the second geometric model of the multi-scale lattice structure. Among them, the second geometric model is in the.stl format, and the.stl format second geometric model is generated by the COMSOL software according to the step generation command flow program for adjusting the first dimension variable and re-writing the command flow program according to the second dimension variable.

[0024] Specifically, use the combined module COMSOL Multiphysics of the SOLIDWORKS software and the COMSOL software to import the first geometric model into the COMSOL software; import the dimension variables of the defined multi-scale lattice structure into the global definition parameter module of the COMSOL software, and change the dimension variables of the multi-scale lattice structure in the global definition parameter module (that is, adjust the first dimension variable of the first geometric model to the second dimension variable) to generate the second geometric model of the multi-scale lattice structure, realizing the reconstruction of the model in SOLIDWORKS, that is, combining SOLIDWORKS and COMSOL to realize the parameterization of the lattice model in COMSOL.

[0025] Step 103: Import the second geometric model into the MATLAB software, and identify the constraint surface and the loading surface of the second geometric model through the MATLAB software.

[0026] In the specific implementation, the COMSOL Multiphysics with MATLAB module is a combined section of COMSOL and MATLAB, which can be used to realize the combination of the two software. The operations in COMSOL can generate a command flow program that can be run by MATLAB, and the operations in COMSOL can be controlled by editing and changing the command flow program. Using this module, in the global definition module of COMSOL, the steps for changing the lattice structure dimensions are output to generate a command flow program, which is output as a program that can be run by MATLAB. To realize the secondary development of the software, that is, to realize the reconstruction of the lattice structure, the program is re-written, and the dimension change is realized through the program, that is, the re-modeling of the lattice structure. In the MATLAB software, only the model in the ".stl" format can be used for finite element analysis. Therefore, the command flow program is changed and written, and the program for saving the lattice structure model is written. The multi-scale lattice model is saved in the ".stl" format through a loop for finite element simulation and analysis. Based on this, the combination of the lattice structure in SOLIDWORKS, COMSOL, and MATLAB is completed, the command flow program is re-written, and the procedural modeling of the additive manufacturing lattice structure at multiple scales is realized.

[0027] Next, complete the parametric simulation of the multi-scale lattice structure in MATLAB: When performing finite element analysis using MATLAB, the ".stl" model needs to be imported. After importing the model, the MATLAB program will automatically number each face of the model to specify the constrained surface and the loaded surface. To achieve the finite element analysis of the multi-scale lattice structure, that is, to achieve parametric modeling and simulation, parametric constraints and loading need to be realized.

[0028] In one example, due to the complex configuration of the additive manufacturing lattice structure, the automatic numbering will change. To solve this problem and realize the simulation of the multi-scale lattice structure, an image recognition technology is proposed to perform image recognition on the numbers of the loaded surface and the constrained surface, and perform loading and constraint through the recognized numbers.

[0029] Specifically, obtain the sample geometric models of the multi-scale lattice structure with numbered constrained surfaces and loaded surfaces, and obtain the images of the constrained surfaces and loaded surfaces of each sample geometric model; among them, each image contains the numbers of the corresponding constrained surface or loaded surface; use the images of the constrained surfaces and loaded surfaces of several sample geometric models to train an image recognition model, and input the images of the constrained surfaces and loaded surfaces of the second geometric model into the image recognition model to obtain the numbers of the constrained surfaces and loaded surfaces of the second geometric model, so as to identify the constrained surfaces and loaded surfaces of the second geometric model.

[0030] In the specific implementation, first automatically number the ".stl" model of the additive manufacturing lattice structure and display the numbered output figure window; then write a program to output the figure window as a picture, crop the picture, crop out the numbers of the surface to be loaded and the constrained surface, and save the cropped picture; put 100 cropped pictures in the Optical Character Recognition (OCR) Trainer section of MATLAB to train the pictures, and write an image recognition program to output the numbers of the loaded surface and the constrained surface.

[0031] Step 104, perform finite element analysis on the second geometric model according to the constrained surface and the loaded surface through MATLAB software to obtain the stress distribution of the multi-scale lattice structure.

[0032] Specifically, write the above image recognition program and the finite element analysis program into an article, use the recognized numbers to perform finite element analysis, output the stress results and stress nephograms, and realize the joint simulation of the parametric modeling of the additive manufacturing lattice structure.

[0033] In one example, after realizing the parametric modeling of the lattice structure, an adaptive line sampling method is proposed to solve the reliability sensitivity, an approximate limit state function is obtained by using the Gaussian process model, and the analysis results of the lattice structure are calculated through the global sensitivity index.

[0034] Specifically, the limit state function of the multi-scale lattice structure is constructed based on the stress distribution of the multi-scale lattice structure. Among them, the limit state function is used to describe whether the multi-scale lattice structure is in a failure state. The Gaussian process model is used as the surrogate model of the limit state function, and the parameter variables that affect the limit state function value of the multi-scale lattice structure are used as sampling points. Through the adaptive line sampling method, sampling is carried out along the important direction, and the Gaussian process model is used to predict the limit state function value at the sampling points. According to the limit state function value, the sampling points that make the multi-scale lattice structure in a failure state are determined as failure samples, and the failure probability of the multi-scale lattice structure is determined according to the number of failure samples.

[0035] In the specific implementation, the input variables in the original space are defined as . To measure the influence of the input variables on the failure probability within the entire distribution range, the concept of global sensitivity is as follows: ; ; In the formula, the input variable refers to the parameter variable that affects the limit state function, represents the th random variable , is the global sensitivity, represents the failure probability, is the failure probability when is a certain value, is the unbiased estimator of the global sensitivity, is the estimator of the failure probability, is the estimator of the joint probability density function of the samples falling into the failure domain, represents the mean value, represents 's joint probability density function.

[0036] The line sampling method is carried out in the standard normal space. The input variables in the original space are subjected to coordinate transformation and converted into the standard normal space. The input variables in the standard normal space are defined as , and the limit state function is defined as . From the joint probability density function of the variables, samples are generated, . Using existing technical means, the important direction and the design point in the standard normal space are solved. Through the corresponding vector transformation, a vector parallel to the unit important direction and passing through the sample point is obtained. vector Specific formulas are as follows: ; In the formula, represents dot product of and represents a vector parallel to vector represents a vector perpendicular to vector

[0037] The problem of solving the failure sample points is transformed into the problem of solving the intersection point between and the limit state function where, represents the coefficient of variation, represents the cumulative distribution function, is the reliability index. The specific steps are as follows:

[0038] Given the coefficient and three initial values , , , a vector passing through the sample point is obtained

[0039] From the formula , the failure probability and the coefficient of variation are calculated

[0040] Three-point quadratic interpolation is performed on the three points to find the point

[0041] Combining the above line sampling method with the Gaussian process model, using the Gaussian process model to approximate the limit state function , predicting the intersection point through adaptive learning, and calculating the failure probability. The learning function of the Gaussian process model is defined as follows: ; In the formula, represents the learning function, represents the probability density of a Gaussian distribution with a mean of and a variance of , represents the estimated value of the limit state function by the Gaussian process model, represents the variance of the Gaussian process model, represents the mean of the Gaussian process model, is the error tolerance used to control the width of the integration interval, and its value should be selected close to the function value at the intersection point​ 10 to 100 times that of

[0042] The specific calculation steps of the adaptive line sampling method are as follows: Define the prediction sample pool , the initial training sample pool , use the function to calculate the response value , from calculate the vector taken by line sampling, and calculate the intersection point corresponding to the initial training sample point .

[0043] From the samples in the training sample pool and their corresponding limit state functions, train the Gaussian process model. According to the Gaussian process model, predict the limit state function values and variances of the samples. When the learning function of the model reaches the stopping threshold , that is , output the result; otherwise, calculate the point with the smallest learning function in the samples, add it to the training sample pool, and continue to train the Gaussian process model. The recommended stopping threshold is selected to be 0.8 - 0.9.

[0044] When the model meets the learning function stopping threshold, that is , calculate the failure probability and its coefficient of variation. When , output the result; otherwise, extract new samples and add them to the prediction sample pool until the stopping condition is met.

[0045] The adaptive line sampling method samples according to the distribution of values. Among them, satisfies the standard normal distribution. According to the intersection point , filter to obtain the samples falling into the failure domain, and use kernel density estimation to calculate the joint probability density and , then the reliability sensitivity can be calculated.

[0046] Therefore, the reliability sensitivity analysis of the lattice structure in this embodiment can be realized through the process shown in Figure 2 as follows: Implement the content of step 101 in SOLIDWORKS software. The improvement of the additive manufacturing lattice structure in step 101 means determining the configuration of the additive manufacturing lattice structure, adding a geometric body with a thickness of 0.05 mm to the loading surface and the constraint surface, and defining the dimensional parameters of the additive manufacturing lattice structure using the equation function. Implement the content of step 102 in COMSOL software to parameterize the additive manufacturing lattice structure in COMSOL, which can be reconstructed by changing parameters, and output the operation steps as a command stream file that can be run by MATLAB. Implement the content of steps 103 and 104 in MATLAB software, write a command stream program to programmatically assign values to the dimensional parameters, write an image recognition and finite element analysis program to achieve parametric modeling and joint simulation of the additive manufacturing lattice structure. Finally, use MATLAB software to write a program for the adaptive line sampling algorithm, construct the failure mode of the lattice structure, propose an adaptive line sampling method to solve the reliability sensitivity, obtain an approximate limit state function using the Gaussian process model, and calculate the analysis results of the lattice structure through the global sensitivity index.

[0047] In this embodiment, by combining SOLIDWORKS, COMSOL, and MATLAB software, the command stream file of COMSOL is recompiled to realize the reconstruction of the model in SOLIDWORKS, reducing the operation difficulty and duration. The image recognition technology is proposed, and MATLAB finite element analysis and image recognition programs are written to achieve parametric modeling and simulation of the multi-scale lattice structure, providing strong support for the reliability analysis of the additive manufacturing lattice structure and improving the actual efficiency. At the same time, an adaptive line sampling method is proposed, which can obtain extremely accurate calculation results at a very small computational cost, greatly reducing the computational cost of traditional reliability analysis. Combining the adaptive surrogate model and the line sampling method realizes global sensitivity analysis in high-dimensional problems, improves the computational efficiency, and provides strong technical support for the reliability analysis of the additive manufacturing lattice structure. In addition, this method can also provide reference for the modeling and reliability sensitivity analysis of other structures.

[0048] A specific embodiment is provided below. Taking the classic L-shaped additive manufacturing lattice structure as an example, joint simulation of parametric modeling of the lattice structure is carried out. In this embodiment, the lattice material is selected as 316L, the left top of the additive manufacturing lattice structure is constrained, and a vertical downward load is applied at the rightmost position.

[0049] Select the L-shaped additive manufacturing lattice structure. The circumscribed cube of this lattice structure is 16.67 mm, the connecting rod diameter is 5 mm, and the overall lattice size is 6 * 6 * 2 units, as Figure 3As shown. The top left end of the additive manufacturing lattice structure is constrained, and a vertically downward load is applied at the rightmost position. The lattice material is 316L steel with a material density of 7.8 g / m 2 , and the limit state function of the lattice structure is defined as , where is the maximum stress, and is the ultimate stress of the material.

[0050] The specific parameter variables are shown in Table 1: Table 1

[0051] Continue to refer to Figure 3 , Figure 3 (a), the target object is an additive manufacturing lattice structure. The overall lattice size is 6 * 6 * 2 units, the connecting rod diameter is 5 mm, the circumscribed cube of the unit cell is 16.67 mm, and a load is applied at the end point. Figure 3 (b), the target object is the geometric modeling diagram of the improved lattice structure, that is, geometries with a thickness of 0.05 mm are added to the loading surface and the constraint surface.

[0052] In this embodiment, the SOLIDWORKS software is used to improve and geometrically model the additive manufacturing lattice structure, and the equation function is used to define the size variables such as the rod diameter and rod length of the additive manufacturing lattice structure to achieve dimensional parameterization; the geometric model of the additive manufacturing lattice structure is imported into the COMSOL software, and the size variables are imported using the combined module COMSOL Multiphysics to achieve parameterization of the additive manufacturing lattice structure within COMSOL. By changing the parameter values in the global definition parameter module, the real-time change of the SOLIDWORKS model can be achieved; in the global definition module of COMSOL, the size variables of the lattice structure are changed, and the command flow program is output. The command flow program is recompiled to reassign the size variables with a loop command to achieve the parametric modeling of the multi-scale lattice structure; a MATLAB image recognition program is written to achieve the number recognition and specification of the constraint surface and the loading surface during the MATLAB simulation of the multi-scale lattice structure. A finite element analysis program is written to achieve the finite element analysis and simulation of the multi-scale additive manufacturing lattice structure in the MATLAB software, output the stress results and stress nephograms, and achieve the combined simulation of the parametric modeling of the additive manufacturing lattice structure; an adaptive line sampling method is proposed to solve the reliability sensitivity, the approximate limit state function is obtained using the Gaussian process model, and the analysis results of the lattice structure are calculated through the global sensitivity index.

[0053] Refer to Figure 4, this figure is the parametric modeling diagram of the unit cell of the lattice structure. In this embodiment, by combining SOLIDWORKS, COMSOL, and MATLAB, and recompiling the COMSOL command flow file and writing the MATLAB program, the parametric modeling and simulation of the multi-scale lattice structure are realized. Figure 4 Specifically, it is the unit cell modeling diagram of the multi-scale lattice structure. Figure 4 The radius of the unit cell of the lattice structure in (a) is 1.6 mm. Figure 4 The radius of the unit cell of the lattice structure in (b) is 0.6 mm.

[0054] See Figure 5 , this figure is the numbering diagram of the unit cell of the lattice structure and the identification diagram of the loading surface numbers of the overall lattice structure. In this embodiment, a MATLAB image recognition program is written to realize the identification and specification of the numbers of the constraint surface and the loading surface during the MATLAB simulation of the multi-scale lattice structure. Figure 5 In (a) is the numbering diagram of the unit cell structure. Figure 5 In (b) is the identification diagram of the loading surface numbers of the overall lattice structure.

[0055] In this embodiment, the finite element analysis of the additive manufacturing lattice structure is carried out using MATLAB software. The tetrahedral elements are used for the finite element mesh division of the structure, and the stress distribution nephogram is drawn.

[0056] After building the parametric modeling platform of the lattice structure, the reliability sensitivity analysis of the lattice structure is carried out. The existing improved first-order second-moment method is used to solve the design point. The adaptive line sampling method is compared with the importance sampling method to solve the reliability and global sensitivity. The results are shown in Table 2, where refers to the number of calls of the limit state function.

[0057] Table 2

[0058] The number of calls of the limit state function by the importance sampling method is 1000 times, and the number of calls of the limit state function by the adaptive line sampling method is 97 times, and it meets the accuracy requirements. The calculation results are stable, and the sensitivity sorting is consistent. This shows that the algorithm has wide applicability and greatly shortens the calculation time. In addition, the adaptive line sampling algorithm is independently repeated ten times to ensure the robustness and convergence of the algorithm. The values in parentheses in the table represent the standard deviation of the results. It can be seen that the present invention can programmatically realize the geometric modeling and finite element analysis of the additive manufacturing lattice structure, reduce the calculation cost, and at the same time ensure the accuracy of the simulation results, proving the effectiveness and efficiency of the method of the present invention.

[0059] The step division of the above various methods is only for clear description. When implemented, they can be combined into one step or some steps can be split into multiple steps. As long as the same logical relationship is included, it is within the protection scope of the present invention; adding insignificant modifications to the algorithm or process or introducing insignificant designs, but without changing the core design of its algorithm and process, is within the protection scope of the invention.

[0060] Another embodiment of the present invention relates to a multi-scale lattice structure parametric modeling device. The implementation details of the multi-scale lattice structure parametric modeling device in this embodiment will be specifically described below. The following content is only the implementation details provided for convenient understanding and is not necessary for implementing this solution. The multi-scale lattice structure parametric modeling device in this embodiment includes: A first model generation module, configured to model the multi-scale lattice structure through SOLIDWORKS software to generate a first geometric model of the multi-scale lattice structure; A second model generation module, configured to import the first geometric model into COMSOL software and adjust the dimension variables of the first geometric model through COMSOL software to generate a second geometric model of the multi-scale lattice structure; wherein, the second geometric model is in.stl format, and the.stl format second geometric model is generated by adopting the command flow program for outputting the first geometric model by COMSOL software and re-writing the command flow program; A model recognition module, configured to import the second geometric model into MATLAB software and identify the constraint surface and the loading surface of the second geometric model through MATLAB software; A model analysis module, configured to perform finite element analysis on the second geometric model according to the constraint surface and the loading surface through MATLAB software to obtain the stress distribution of the multi-scale lattice structure.

[0061] In an example, the multi-scale lattice structure parametric modeling device of the present invention includes: A parametric modeling module: improving and geometrically modeling the additive manufacturing lattice structure by using SOLIDWORKS software and realizing dimension parameterization; importing the geometric model of the additive manufacturing lattice structure into COMSOL software and importing dimension variables by using the combined module COMSOL Multiphysics to realize the parameterization of the additive manufacturing lattice structure in COMSOL; in the global definition module of COMSOL, changing the dimension variables of the lattice structure, outputting a command flow program, re-writing the command flow program, and re-assigning the dimension variables with a loop command to realize the parametric modeling of the multi-scale lattice structure; Parametric co-simulation module: Write a MATLAB image recognition program to achieve the number recognition and specification of the constraint surface and the loading surface during the MATLAB simulation of the multi-scale lattice structure. Write a finite element analysis program to achieve the parametric finite element analysis of the multi-scale lattice structure.

[0062] Reliability sensitivity analysis module: Propose an adaptive line sampling method to solve the reliability sensitivity. Use the Gaussian process model to obtain an approximate limit state function, and calculate the analysis results of the lattice structure through the global sensitivity index.

[0063] It is not difficult to find that this embodiment is a device embodiment corresponding to the above method embodiment, and this embodiment can be implemented in cooperation with the above method embodiment. The relevant technical details and technical effects mentioned in the above embodiments are still valid in this embodiment. To avoid repetition, they will not be elaborated here. Correspondingly, the relevant technical details mentioned in this embodiment can also be applied to the above embodiments.

[0064] It is worth mentioning that each module involved in this embodiment is a logical module. In practical applications, a logical unit can be a physical unit, a part of a physical unit, or a combination of multiple physical units. In addition, to highlight the innovative part of the present invention, units that are not closely related to solving the technical problems proposed by the present invention are not introduced in this embodiment, but this does not mean that there are no other units in this embodiment.

[0065] Another embodiment of the present invention relates to a computer device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the parametric modeling method of the multi-scale lattice structure in the above embodiments.

[0066] Among them, the memory and the processor are connected in a bus manner. The bus can include any number of interconnected buses and bridges, and the bus connects various circuits of one or more processors and the memory together. The bus can also connect various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art, so they will not be further described herein. The bus interface provides an interface between the bus and the transceiver. The transceiver can be an element or multiple elements, such as multiple receivers and transmitters, and provides a unit for communicating with various other devices on the transmission medium. The data processed by the processor is transmitted over the wireless medium through the antenna. Further, the antenna also receives data and transmits the data to the processor.

[0067] The processor is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interfaces, voltage regulation, power management, and other control functions. The memory can be used to store the data used by the processor during operation.

[0068] Another embodiment of the present invention relates to a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the method embodiments described above are implemented.

[0069] That is, those skilled in the art can understand that all or part of the steps in implementing the methods of the above embodiments can be completed by instructing relevant hardware through a program. The program is stored in a storage medium, including several instructions for causing a device (which can be a single-chip microcomputer, a chip, etc.) or a processor to execute all or part of the steps of the methods described in the various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical discs that can store program codes.

[0070] Those of ordinary skill in the art can understand that the above embodiments are specific embodiments for implementing the present invention, and in practical applications, various changes can be made in form and details without departing from the spirit and scope of the present invention.

Claims

1. A parametric modeling method for multi-scale lattice structures, characterized in that, The method includes: Modeling the multi-scale lattice structure through SOLIDWORKS software to generate a first geometric model of the multi-scale lattice structure; Importing the first geometric model into COMSOL software, and adjusting the first dimension variable of the first geometric model to a second dimension variable through COMSOL software to generate a second geometric model of the multi-scale lattice structure; wherein, the second geometric model is in.stl format, and the.stl format second geometric model is generated by COMSOL software according to the steps of adjusting the first dimension variable to generate a command flow program and re-writing the command flow program according to the second dimension variable; Importing the second geometric model into MATLAB software, and identifying the constraint surface and the loading surface of the second geometric model through MATLAB software; Performing finite element analysis on the second geometric model according to the constraint surface and the loading surface through MATLAB software to obtain the stress distribution of the multi-scale lattice structure.

2. The parametric modeling method for the multi-scale lattice structure according to claim 1, wherein The modeling the multi-scale lattice structure through SOLIDWORKS software to generate a first geometric model of the multi-scale lattice structure includes: Modeling according to the geometric configuration of the multi-scale lattice structure using SOLIDWORKS software, and during the modeling process, defining the first dimension variable of the multi-scale lattice structure using the equation function within SOLIDWORKS software to generate the first geometric model.

3. The parametric modeling method for the multi-scale lattice structure according to claim 2, wherein The importing the first geometric model into COMSOL software, and adjusting the first dimension variable of the first geometric model to a second dimension variable through COMSOL software to generate a second geometric model of the multi-scale lattice structure includes: Using the combined module COMSOL Multiphysics of SOLIDWORKS software and COMSOL software to import the first geometric model into COMSOL software; Importing the defined first dimension variable of the multi-scale lattice structure into the global definition parameter module of COMSOL software, and generating a command flow file for the steps of setting parameters in the global definition parameter module; Re-writing the command flow program to adjust the first dimension variable of the first geometric model to the second dimension variable to generate a second geometric model of the multi-scale lattice structure.

4. The parametric modeling method of the multi-scale lattice structure according to claim 1, wherein The identifying the constraint surface and the loading surface of the second geometric model through MATLAB software includes: Obtaining sample geometric models of the multi-scale lattice structure with numbers for a plurality of constraint surfaces and loading surfaces, and obtaining images of the constraint surfaces and loading surfaces of each sample geometric model; wherein, each image contains the number corresponding to the constraint surface or the loading surface; Training an image recognition model using the images of the constraint surfaces and loading surfaces of a plurality of sample geometric models, and inputting the images of the constraint surfaces and loading surfaces of the second geometric model into the image recognition model to obtain the numbers of the constraint surfaces and loading surfaces of the second geometric model, so as to identify the constraint surfaces and loading surfaces of the second geometric model.

5. The parametric modeling method for the multi-scale lattice structure according to claim 1, wherein After obtaining the stress distribution of the multi-scale lattice structure, it further includes: Construct the limit state function of the multi-scale lattice structure according to the stress distribution; wherein, the limit state function is used to describe whether the multi-scale lattice structure is in a failure state; Use the Gaussian process model as the surrogate model of the limit state function, take the parameter variables that affect the limit state function value of the multi-scale lattice structure as sampling points, sample along the important direction by the adaptive line sampling method, and use the Gaussian process model to predict the limit state function value at the sampling points; Determine the sampling points that make the multi-scale lattice structure in a failure state according to the limit state function value as failure samples, and determine the failure probability of the multi-scale lattice structure according to the number of failure samples.

6. A multi-scale lattice structure parametric modeling device, characterized in that, The device includes: A first model generation module, configured to model the multi-scale lattice structure through SOLIDWORKS software to generate a first geometric model of the multi-scale lattice structure; A second model generation module, configured to import the first geometric model into COMSOL software, and adjust the first size variable of the first geometric model to a second size variable through COMSOL software to generate a second geometric model of the multi-scale lattice structure; wherein, the second geometric model is in.stl format, and the.stl format second geometric model is generated by COMSOL software according to the steps of adjusting the first size variable to generate a command flow program and re-writing the command flow program according to the second size variable; A model recognition module, configured to import the second geometric model into MATLAB software, and identify the constraint surface and the loading surface of the second geometric model through MATLAB software; A model analysis module, configured to perform finite element analysis on the second geometric model according to the constraint surface and the loading surface through MATLAB software to obtain the stress distribution of the multi-scale lattice structure.

7. A computer device, characterized in that, Includes: At least one processor; And a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the multi-scale lattice structure parametric modeling method according to any one of claims 1 to 5.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the multi-scale lattice structure parametric modeling method according to any one of claims 1 to 5.

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